PCA-based reconstruction of exogenous inputs, with a dynamic 90% variance component count, improves transformer forecasting MSE on ETTm1, ETTm2, ETTh1, and Weather, but not on ECL, ETTh2, or Traffic.
Traffic flow prediction with big data: A deep learning approach,
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Temporal Window Smoothing of Exogenous Variables for Improved Time Series Prediction
PCA-based reconstruction of exogenous inputs, with a dynamic 90% variance component count, improves transformer forecasting MSE on ETTm1, ETTm2, ETTh1, and Weather, but not on ECL, ETTh2, or Traffic.